A Review of Nutrient Management Studies Involving Finger Millet in the Semi-Arid Tropics of Asia and Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Finger millet (Eleusine coracana (L.) Gaertn) is a staple food crop grown by subsistence farmers in the semi-arid tropics of South Asia and Africa. It remains highly valued by traditional farmers as it is nutritious, drought tolerant, short duration, and requires low inputs. Its continued propagation may help vulnerable farmers mitigate climate change. Unfortunately, the land area cultivated with this crop has decreased, displaced by maize and rice. Reversing this trend will involve achieving higher yields, including through improvements in crop nutrition. The objective of this paper is to comprehensively review the literature concerning yield responses of finger millet to inorganic fertilizers (macronutrients and micronutrients), farmyard manure (FYM), green manures, organic by-products, and biofertilizers. The review also describes the impact of these inputs on soils, as well as the impact of diverse cropping systems and finger millet varieties, on nutrient responses. The review critically evaluates the benefits and challenges associated with integrated nutrient management, appreciating that most finger millet farmers are economically poor and primarily use farmyard manure. We conclude by identifying research gaps related to nutrient management in finger millet, and provide recommendations to increase the yield and sustainability of this crop as a guide for subsistence farmers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it